Dr. Boleslaw K. Szymanski presented a paper titled “Mining personal media thresholds for opinion dynamics and social influence” co-authored by Casey Doyley, Alex Meandzijay, and Gyorgy Korniss of RPI and Derrik Asher, and Elizabeth Bowman of ARL at the Social Influence Workshop, a part of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) in Barcelona, Spain, August 28, 2018. The excerpt from the abstract is provided here. To study the detailed effects of social media consumption on personal opinion dynamics, the paper discusses self-reported survey data on the volume of different media types an individual must consume before forming or changing their opinion on a subject. Then, the frequent pattern mining is used to analyze the data for common groupings of responses with respect to various media types, sources, and contexts. The paper shows that in general individuals tend to perceive their behavior to be consistent across many variations in these parameters. Further detail shows various common parameter groupings that indicate response changes as well as small groups of individuals that tend to be consistently more easily swayed than the average participant.

The paper has been published in the Proceedings of ASONAM and is available at the link provided below.